It is of great value for medical doctors to be able to peer into our bodies in a non-invasive and safe manner when diagnosing patients. Ultrasound imaging fulfills this need and also offers an important imaging technique used in IGS (image guided surgery). Performing open surgery on a patient involves great risk and is often followed by a long hospitalization time. IGS enables minimally invasive procedures where surgical instruments are safely maneuvered with the help of imaging technology into the targeted area of the human body. By reconstructing a 3D volume from ultrasound scans, the internals of a patient can be visualized in ways not possible by scans alone, enabling image guidance and diagnostics. Both the reconstruction and visualization is computationally intensive, and it is desirable to see the constructed volume while it is being built.

Reconstruction using existing methods can take minutes if not hours. Reducing this process to only seconds would enable instant feedback \emph{during} critical surgical operations. Furthermore, incremental reconstruction while the data is acquired makes it possible to rescan areas of interest as observed on simultaneous real-time visualization. In this thesis, we evaluate how GPUs (graphical processing units) can be utilized to perform fast 3D ultrasound reconstruction and visualization, and present methods for incremental and non-incremental reconstruction with simultaneous visualization on the GPU.